{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c074fe6e",
   "metadata": {},
   "source": [
    "**<font size=4 color=#BB3D00 face=微软雅黑>多通道输入的互相关</font>**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b61675c",
   "metadata": {},
   "source": [
    "<font size=3  face=微软雅黑>**※Matlab案例**</font> "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82cccac7",
   "metadata": {},
   "source": [
    "网址：https://ww2.mathworks.cn/help/signal/ug/cross-correlation-with-multichannel-input.html   \n",
    "描述：本案例由2个示例构成：   \n",
    "- <font color=DarkOrChid>示例1：生成三个包含 11 个样本的指数序列</font>\n",
    "- <font color=DarkOrChid>示例2：计算这些序列的自相关和互相关</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4bfd5da",
   "metadata": {},
   "source": [
    "<font size=3 face=微软雅黑>**※Python案例**</font> "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6e1956f",
   "metadata": {},
   "source": [
    "针对以上案例，采用Python语言实现。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "754875e4",
   "metadata": {},
   "source": [
    "- <font color=DarkOrChid>示例1：生成三个包含 11 个样本的指数序列</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86a45347",
   "metadata": {},
   "source": [
    "生成三个包含 11 个样本的指数序列，这些样本由$0.4^{n}$、$0.7^{n}$和$0.999^{n}$ $(n\\geq0)$给出。绘制这些序列。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "091c3f31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np  \n",
    "import matplotlib.pyplot as plt \n",
    "\n",
    "x = np.arange(0,11)  \n",
    "y1 = 0.4**x \n",
    "y2 = 0.7**x \n",
    "y3 = 0.999**x \n",
    "fig = plt.figure()  \n",
    "ax1 = fig.add_subplot(111)   \n",
    "ax1.scatter(x,y1,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1.2)\n",
    "plt.show()\n",
    "fig = plt.figure()  \n",
    "ax1 = fig.add_subplot(111)   \n",
    "ax1.scatter(x,y2,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1.2)\n",
    "plt.show()\n",
    "fig = plt.figure()  \n",
    "ax1 = fig.add_subplot(111)   \n",
    "ax1.scatter(x,y3,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45b1295d",
   "metadata": {},
   "source": [
    "- <font color=DarkOrChid>示例2：计算这些序列的自相关和互相关</font>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee563634",
   "metadata": {},
   "source": [
    "计算这些序列的自相关和互相关。输出滞后，这样您就不必跟踪它们。将结果归一化，使自相关在零滞后处具有单位值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7b7a6d42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1200 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cx=np.arange(-10,11)\n",
    "cq11=np.correlate(y1,y1,'full')\n",
    "cq12=np.correlate(y1,y2,'full')\n",
    "cq13=np.correlate(y1,y3,'full')\n",
    "cq21=np.correlate(y2,y1,'full')\n",
    "cq22=np.correlate(y2,y2,'full')\n",
    "cq23=np.correlate(y2,y3,'full')\n",
    "cq31=np.correlate(y3,y1,'full')\n",
    "cq32=np.correlate(y3,y2,'full')\n",
    "cq33=np.correlate(y3,y3,'full')\n",
    "c11=cq11/cq11[10]\n",
    "c12=cq12/(cq11[10]*cq22[10])**0.5\n",
    "c13=cq13/(cq11[10]*cq33[10])**0.5\n",
    "c21=cq21/(cq11[10]*cq22[10])**0.5\n",
    "c22=cq22/cq22[10]\n",
    "c23=cq23/(cq33[10]*cq22[10])**0.5\n",
    "c31=cq31/(cq11[10]*cq33[10])**0.5\n",
    "c32=cq32/(cq33[10]*cq22[10])**0.5\n",
    "c33=cq33/cq33[10]\n",
    "fig = plt.figure(dpi=300,figsize=(8,4))  \n",
    "ax1 = fig.add_subplot(331)   \n",
    "ax1.set_title('C$_{11}$')\n",
    "ax1.scatter(cx,c11,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(332)   \n",
    "ax1.set_title('C$_{12}$')\n",
    "ax1.scatter(cx,c12,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(333)   \n",
    "ax1.set_title('C$_{13}$')\n",
    "ax1.scatter(cx,c13,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(334)   \n",
    "ax1.set_title('C$_{21}$')\n",
    "ax1.scatter(cx,c21,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(335)   \n",
    "ax1.set_title('C$_{22}$')\n",
    "ax1.scatter(cx,c22,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(336)   \n",
    "ax1.set_title('C$_{23}$')\n",
    "ax1.scatter(cx,c23,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1) \n",
    "ax1 = fig.add_subplot(337)   \n",
    "ax1.set_title('C$_{31}$')\n",
    "ax1.scatter(cx,c31,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(338)   \n",
    "ax1.set_title('C$_{32}$')\n",
    "ax1.scatter(cx,c32,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "ax1 = fig.add_subplot(339)   \n",
    "ax1.set_title('C$_{33}$')\n",
    "ax1.scatter(cx,c33,c = 'r',marker = 'o')  \n",
    "plt.ylim(-0.2,1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "464215ad",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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